Asymptotic Inference for Jump Diffusions with State-Dependent Intensity

37 Pages Posted: 11 Jul 2013 Last revised: 13 Feb 2015

See all articles by I. Gaia Becheri

I. Gaia Becheri

Delft University of Technology

Feike C. Drost

Tilburg University - Center for Economic Research (CentER)

Bas J. M. Werker

Tilburg University - Center for Economic Research (CentER)

Date Written: December 2014

Abstract

We establish the Local Asymptotic Normality (LAN) property for a class of parametric jump-diffusion processes with state-dependent intensity and known volatility function sampled at high-frequency. We prove that the inference problem about the drift and jump parameters is adaptive with respect to parameters in the volatility function that can be consistently estimated.

Suggested Citation

Becheri, I. Gaia and Drost, Feike C. and Werker, Bas J.M., Asymptotic Inference for Jump Diffusions with State-Dependent Intensity (December 2014). Available at SSRN: https://ssrn.com/abstract=2292486 or http://dx.doi.org/10.2139/ssrn.2292486

I. Gaia Becheri

Delft University of Technology ( email )

Stevinweg 1
Stevinweg 1
Delft, 2628 CN
Netherlands

Feike C. Drost

Tilburg University - Center for Economic Research (CentER) ( email )

Econometrics and Finance Group
P.O. Box 90153
5000 LE Tilburg
Netherlands
+31 13 466 3038 (Phone)

Bas J.M. Werker (Contact Author)

Tilburg University - Center for Economic Research (CentER) ( email )

Econometrics and Finance Group
5000 LE Tilburg
Netherlands

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